Effects of variable-time impulses on global exponential stability of Cohen-Grossberg neural networks

作     者：Xianxiu Zhang Chuandong Li Tingwen Huang Hafiz Gulfam Ahmad 

作者机构：College of Electronic and Information EngineeringSouthwest University Chongqing 400715 P. R. China Department of Mathematics Liupanshui Normal University Guizhou Liupanshui 553001 P. R. China Department of MathematicsTexas A&M University at Qatar Doha 23874 Qatar Department of Computer Science and ITGhazi University D. G. Khan 32260 Pakistan 

出 版 物：《International Journal of Biomathematics》 (生物数学学报（英文版）)

年 卷 期：2017年第10卷第8期

页      面：241-263页

核心收录：

学科分类：05[文学] 0701[理学-数学] 0503[文学-新闻传播学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Science and Technology Fund of Guizhou Province, (7612) Qatar Foundation, QF Qatar National Research Fund, QNRF National Natural Science Foundation of China, NSFC, (61374078) Chongqing Research Program of Basic Research and Frontier Technology, (4-1162-1-181, cstc2015jcyjBX0052) 

主　　题：Cohen–Grossberg neural network (CGNN) variable-time impulse B-equivalence global exponential stability 

摘      要：We investigate the global exponential stability of Cohen–Grossberg neural networks (CGNNs) with variable moments of impulses using B-equivalence method. Under certain conditions, we show that each solution of the considered system intersects each surface of discontinuity exactly once, and that the variable-time impulsive systems can be reduced to the fixed-time impulsive ones. The obtained results imply that impulsive CGNN will remain stability property of continuous subsystem even if the impulses are of somewhat destabilizing, and that stabilizing impulses can stabilize the unstable continuous subsystem at its equilibrium points. Moreover, two stability criteria for the considered CGNN by use of proposed comparison system are obtained. Finally, the theoretical results are illustrated by two examples.